Probability-based software has been developed for identifying proteins separated by 2-dimensional electrophoresis. The identification of isolated proteins is an important requirement for many biological investigations. Database searching using mass spectrometric peptide mapping has proved to be a sensitive and facile method for protein identification. The method involves comparison of masses obtained in peptide mapping experiment with the masses calculated by applying the appropriate cleavage rule to each protein in a protein sequence database. The objective of the present work was to use a Bayesian algorithm to rank the candidate proteins with probability. A highly efficient algorithm was developed and was made publicly available over the world wide web together with an extensive set of tools for evaluating the results of the search (SEE HIGHLIGHT #2)